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Soil Quality Evaluation Based on A Minimum Data Set (MDS)—A Case Study of Tieling County, Northeast China
Version 1
: Received: 26 April 2023 / Approved: 27 April 2023 / Online: 27 April 2023 (03:46:54 CEST)
A peer-reviewed article of this Preprint also exists.
Qian, F.; Yu, Y.; Dong, X.; Gu, H. Soil Quality Evaluation Based on a Minimum Data Set (MDS)—A Case Study of Tieling County, Northeast China. Land 2023, 12, 1263. Qian, F.; Yu, Y.; Dong, X.; Gu, H. Soil Quality Evaluation Based on a Minimum Data Set (MDS)—A Case Study of Tieling County, Northeast China. Land 2023, 12, 1263.
Abstract
Soil quality is related to food security and human survival and development. In recent years, due to the acceleration of urbanization and the increase of abandoned land, land degradation occurs, poor topsoil quality. In this study, the minimum data set (MDS) was constructed through principal component analysis (PCA) to determine the indicator data set for evaluating topsoil quality in Tieling County, China. In addition, the soil quality index (SQI) was calculated to analyze the spatial distribution characteristics and influencing reasons of topsoil quality in Tieling County. The re-sults showed that MDS included total potassium (TK), Clay, zinc (Zn), soil organic matter (SOM), soil water content (SWC), cation exchange capacity (CEC), pH, and copper (Cu). The MDS indicators can well replace all indicators to evaluate the topsoil quality in the study area. The overall soil quality of Tieling County showed a trend of low in the east and high in the west, and gradually increased from the hilly area to the plain area. The evaluation results are consistent with field research, which can provide reference for other topsoil quality evaluation, and it also provide a basis for the formulation of soil quality improvement measures.
Keywords
soil quality assessment; minimum data set; soil quality index; principal component analysis
Subject
Environmental and Earth Sciences, Soil Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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